Overview

Dataset statistics

Number of variables19
Number of observations2405
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory359.3 KiB
Average record size in memory153.0 B

Variable types

DateTime1
TimeSeries15
Boolean1
Numeric2

Timeseries statistics

Number of series15
Time series length2405
Starting point2010-01-26 00:00:00
Ending point2019-08-19 00:00:00
Period1 day, 10 hours and 51 minutes
2026-02-01T22:33:51.967162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:52.261873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
AD is highly overall correlated with EMA and 7 other fieldsHigh correlation
ATR is highly overall correlated with NATR and 2 other fieldsHigh correlation
CMO is highly overall correlated with ROC and 1 other fieldsHigh correlation
EMA is highly overall correlated with AD and 6 other fieldsHigh correlation
KAMA is highly overall correlated with AD and 6 other fieldsHigh correlation
MA is highly overall correlated with AD and 6 other fieldsHigh correlation
MidPrice is highly overall correlated with AD and 6 other fieldsHigh correlation
NATR is highly overall correlated with ATR and 1 other fieldsHigh correlation
OBV is highly overall correlated with AD and 1 other fieldsHigh correlation
ROC is highly overall correlated with CMO and 1 other fieldsHigh correlation
TRANGE is highly overall correlated with ATR and 1 other fieldsHigh correlation
TSF is highly overall correlated with AD and 6 other fieldsHigh correlation
WILLR is highly overall correlated with CMO and 1 other fieldsHigh correlation
WMA is highly overall correlated with AD and 6 other fieldsHigh correlation
close is highly overall correlated with AD and 6 other fieldsHigh correlation
close is non stationaryNon stationary
MA is non stationaryNon stationary
EMA is non stationaryNon stationary
KAMA is non stationaryNon stationary
WMA is non stationaryNon stationary
MidPrice is non stationaryNon stationary
AD is non stationaryNon stationary
OBV is non stationaryNon stationary
NATR is non stationaryNon stationary
ATR is non stationaryNon stationary
TSF is non stationaryNon stationary
close is seasonalSeasonal
MA is seasonalSeasonal
EMA is seasonalSeasonal
KAMA is seasonalSeasonal
WMA is seasonalSeasonal
MidPrice is seasonalSeasonal
AD is seasonalSeasonal
OBV is seasonalSeasonal
NATR is seasonalSeasonal
ATR is seasonalSeasonal
Date has unique valuesUnique
EMA has unique valuesUnique
KAMA has unique valuesUnique
NATR has unique valuesUnique
ATR has unique valuesUnique
BOP has 372 (15.5%) zerosZeros
WILLR has 72 (3.0%) zerosZeros

Reproduction

Analysis started2026-02-02 04:33:30.665956
Analysis finished2026-02-02 04:33:51.765251
Duration21.1 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
Minimum2010-01-26 00:00:00
Maximum2019-08-19 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T22:33:52.409176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:52.588745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct629
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.6794
Minimum1051
Maximum1889
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:52.695356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1051
5-th percentile1118.2
Q11224
median1290
Q31405
95-th percentile1720.8
Maximum1889
Range838
Interquartile range (IQR)181

Descriptive statistics

Standard deviation179.87752
Coefficient of variation (CV)0.13396908
Kurtosis0.06445027
Mean1342.6794
Median Absolute Deviation (MAD)79
Skewness0.99319826
Sum3229144
Variance32355.923
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2770123027
2026-02-01T22:33:52.792092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:53.049269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:33:53.829664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
124419
 
0.8%
128618
 
0.7%
127217
 
0.7%
122417
 
0.7%
132415
 
0.6%
122615
 
0.6%
123415
 
0.6%
126615
 
0.6%
122914
 
0.6%
131614
 
0.6%
Other values (619)2246
93.4%
ValueCountFrequency (%)
10511
 
< 0.1%
10521
 
< 0.1%
10541
 
< 0.1%
10561
 
< 0.1%
10602
0.1%
10622
0.1%
10631
 
< 0.1%
10641
 
< 0.1%
10651
 
< 0.1%
10663
0.1%
ValueCountFrequency (%)
18891
< 0.1%
18741
< 0.1%
18701
< 0.1%
18581
< 0.1%
18561
< 0.1%
18541
< 0.1%
18491
< 0.1%
18281
< 0.1%
18272
0.1%
18261
< 0.1%
2026-02-01T22:33:52.875082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.1 KiB
False
2405 
ValueCountFrequency (%)
False2405
100.0%
2026-02-01T22:33:54.212982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

MA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1848
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.9374
Minimum1066.7
Maximum1838.6
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:54.394142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1066.7
5-th percentile1117.54
Q11223.7
median1290.7
Q31397.7
95-th percentile1720.14
Maximum1838.6
Range771.9
Interquartile range (IQR)174

Descriptive statistics

Standard deviation179.13815
Coefficient of variation (CV)0.13349218
Kurtosis0.03241805
Mean1341.9374
Median Absolute Deviation (MAD)77.8
Skewness0.99489693
Sum3227359.4
Variance32090.477
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4563569284
2026-02-01T22:33:54.490629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:54.736922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:33:55.371909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
12985
 
0.2%
1211.25
 
0.2%
1255.55
 
0.2%
1225.25
 
0.2%
1226.95
 
0.2%
1216.14
 
0.2%
1251.94
 
0.2%
1276.94
 
0.2%
12564
 
0.2%
1296.34
 
0.2%
Other values (1838)2360
98.1%
ValueCountFrequency (%)
1066.71
< 0.1%
1067.32
0.1%
1067.41
< 0.1%
1068.21
< 0.1%
1068.61
< 0.1%
1068.81
< 0.1%
1068.92
0.1%
1069.61
< 0.1%
1069.91
< 0.1%
1070.32
0.1%
ValueCountFrequency (%)
1838.61
< 0.1%
1838.31
< 0.1%
1834.71
< 0.1%
1833.31
< 0.1%
1833.11
< 0.1%
1831.91
< 0.1%
1823.51
< 0.1%
1822.11
< 0.1%
1819.81
< 0.1%
1817.91
< 0.1%
2026-02-01T22:33:54.569602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

EMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.9647
Minimum1066.7703
Maximum1835.217
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:55.863089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1066.7703
5-th percentile1117.5624
Q11223.5239
median1290.4174
Q31397.0766
95-th percentile1719.1476
Maximum1835.217
Range768.44675
Interquartile range (IQR)173.55264

Descriptive statistics

Standard deviation178.72787
Coefficient of variation (CV)0.13318374
Kurtosis0.010192308
Mean1341.9647
Median Absolute Deviation (MAD)76.76396
Skewness0.99360199
Sum3227425.1
Variance31943.652
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3079057431
2026-02-01T22:33:55.965223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:56.221061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:33:56.870801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1111.4562151
 
< 0.1%
1106.4641761
 
< 0.1%
1102.379781
 
< 0.1%
1098.8561841
 
< 0.1%
1099.7914231
 
< 0.1%
1102.9202551
 
< 0.1%
1104.38931
 
< 0.1%
1096.6821541
 
< 0.1%
1088.5581261
 
< 0.1%
1084.4566491
 
< 0.1%
Other values (2395)2395
99.6%
ValueCountFrequency (%)
1066.7702781
< 0.1%
1067.6880591
< 0.1%
1067.830341
< 0.1%
1068.0631831
< 0.1%
1068.5155451
< 0.1%
1069.6945371
< 0.1%
1069.9029551
< 0.1%
1070.290231
< 0.1%
1070.4078881
< 0.1%
1070.4894471
< 0.1%
ValueCountFrequency (%)
1835.2170251
< 0.1%
1830.6321111
< 0.1%
1830.5985861
< 0.1%
1829.9717271
< 0.1%
1828.8859591
< 0.1%
1827.9312211
< 0.1%
1825.3982721
< 0.1%
1819.6339661
< 0.1%
1818.5826031
< 0.1%
1818.2459721
< 0.1%
2026-02-01T22:33:56.049287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

KAMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.8329
Minimum1071.387
Maximum1818.3649
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:57.376329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1071.387
5-th percentile1112.3884
Q11221.3696
median1292.1151
Q31401.4626
95-th percentile1720.7517
Maximum1818.3649
Range746.9779
Interquartile range (IQR)180.09297

Descriptive statistics

Standard deviation180.56052
Coefficient of variation (CV)0.13446238
Kurtosis-0.019440933
Mean1342.8329
Median Absolute Deviation (MAD)78.266263
Skewness0.98439774
Sum3229513.2
Variance32602.101
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.31251251
2026-02-01T22:33:57.478408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:57.732142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:33:58.375128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1120.8069371
 
< 0.1%
1117.3009581
 
< 0.1%
1112.8500491
 
< 0.1%
1107.2488471
 
< 0.1%
1107.1025361
 
< 0.1%
1107.4657851
 
< 0.1%
1107.4838211
 
< 0.1%
1104.4348131
 
< 0.1%
1101.2706691
 
< 0.1%
1099.8904771
 
< 0.1%
Other values (2395)2395
99.6%
ValueCountFrequency (%)
1071.3870231
< 0.1%
1071.5258381
< 0.1%
1071.5275991
< 0.1%
1071.5462151
< 0.1%
1071.5507091
< 0.1%
1071.6194981
< 0.1%
1071.6766261
< 0.1%
1071.6866011
< 0.1%
1071.7014241
< 0.1%
1071.716531
< 0.1%
ValueCountFrequency (%)
1818.3649231
< 0.1%
1818.3349281
< 0.1%
1818.2058161
< 0.1%
1818.117061
< 0.1%
1817.0779441
< 0.1%
1817.0340291
< 0.1%
1814.0811571
< 0.1%
1813.9914561
< 0.1%
1813.748291
< 0.1%
1813.6944831
< 0.1%
2026-02-01T22:33:57.562927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WMA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2284
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.1776
Minimum1063.5091
Maximum1843.3636
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:59.000125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1063.5091
5-th percentile1116.3091
Q11223.5455
median1290.2545
Q31401.0545
95-th percentile1719.4655
Maximum1843.3636
Range779.85455
Interquartile range (IQR)177.50909

Descriptive statistics

Standard deviation179.24437
Coefficient of variation (CV)0.13354743
Kurtosis0.03531598
Mean1342.1776
Median Absolute Deviation (MAD)77.890909
Skewness0.9935209
Sum3227937.1
Variance32128.544
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2907798004
2026-02-01T22:33:59.104613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:59.377502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:00.183786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1332.7272733
 
0.1%
1301.3090913
 
0.1%
1293.6727273
 
0.1%
1296.4909093
 
0.1%
1200.3454553
 
0.1%
1293.5818183
 
0.1%
1343.63
 
0.1%
1244.0363643
 
0.1%
1249.9090912
 
0.1%
1224.2545452
 
0.1%
Other values (2274)2377
98.8%
ValueCountFrequency (%)
1063.5090911
< 0.1%
1064.4909091
< 0.1%
1066.6545451
< 0.1%
1067.21
< 0.1%
1067.5090911
< 0.1%
1068.2363641
< 0.1%
1068.4545451
< 0.1%
1068.6181821
< 0.1%
1068.9090911
< 0.1%
1069.6181821
< 0.1%
ValueCountFrequency (%)
1843.3636361
< 0.1%
1839.1636361
< 0.1%
1837.7636361
< 0.1%
1837.4545451
< 0.1%
1835.1090911
< 0.1%
1830.81
< 0.1%
1830.0909091
< 0.1%
1824.1454551
< 0.1%
1823.3636361
< 0.1%
1821.6727271
< 0.1%
2026-02-01T22:33:59.199481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MidPrice
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct792
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.4663
Minimum1064.5
Maximum1852.5
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:00.872643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1064.5
5-th percentile1119.5
Q11223
median1292
Q31398
95-th percentile1716.3
Maximum1852.5
Range788
Interquartile range (IQR)175

Descriptive statistics

Standard deviation178.10345
Coefficient of variation (CV)0.13276774
Kurtosis0.03804421
Mean1341.4663
Median Absolute Deviation (MAD)79.5
Skewness0.9916856
Sum3226226.5
Variance31720.84
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2783140771
2026-02-01T22:34:00.969426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:01.214820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:01.870157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
124022
 
0.9%
1202.517
 
0.7%
127616
 
0.7%
1295.513
 
0.5%
1284.513
 
0.5%
1276.512
 
0.5%
120112
 
0.5%
127112
 
0.5%
132312
 
0.5%
128411
 
0.5%
Other values (782)2265
94.2%
ValueCountFrequency (%)
1064.51
 
< 0.1%
10662
 
0.1%
1066.51
 
< 0.1%
10671
 
< 0.1%
1067.59
0.4%
10683
 
0.1%
1069.51
 
< 0.1%
1071.52
 
0.1%
1074.54
0.2%
10761
 
< 0.1%
ValueCountFrequency (%)
1852.51
 
< 0.1%
1847.52
 
0.1%
18441
 
< 0.1%
18403
0.1%
1824.52
 
0.1%
1816.52
 
0.1%
1809.53
0.1%
18087
0.3%
1807.51
 
< 0.1%
18061
 
< 0.1%
2026-02-01T22:34:01.050505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

BOP
Real number (ℝ)

Zeros 

Distinct471
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0028300267
Minimum-2.6666667
Maximum2.6666667
Zeros372
Zeros (%)15.5%
Negative1026
Negative (%)42.7%
Memory size37.6 KiB
2026-02-01T22:34:02.344389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.6666667
5-th percentile-1
Q1-0.5
median0
Q30.5
95-th percentile0.9952381
Maximum2.6666667
Range5.3333333
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.60190693
Coefficient of variation (CV)-212.68595
Kurtosis-0.68445918
Mean-0.0028300267
Median Absolute Deviation (MAD)0.5
Skewness0.03727307
Sum-6.8062143
Variance0.36229195
MonotonicityNot monotonic
2026-02-01T22:34:02.421841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0372
 
15.5%
-1123
 
5.1%
1114
 
4.7%
-0.557
 
2.4%
0.549
 
2.0%
0.333333333343
 
1.8%
-0.666666666736
 
1.5%
-0.2528
 
1.2%
-0.333333333327
 
1.1%
0.7526
 
1.1%
Other values (461)1530
63.6%
ValueCountFrequency (%)
-2.6666666671
 
< 0.1%
-1.6666666671
 
< 0.1%
-1.2580645161
 
< 0.1%
-1.1111111111
 
< 0.1%
-1123
5.1%
-0.98019801981
 
< 0.1%
-0.97777777781
 
< 0.1%
-0.97142857141
 
< 0.1%
-0.968751
 
< 0.1%
-0.96774193551
 
< 0.1%
ValueCountFrequency (%)
2.6666666671
 
< 0.1%
2.3333333331
 
< 0.1%
21
 
< 0.1%
1.6111111111
 
< 0.1%
1.251
 
< 0.1%
1.1538461541
 
< 0.1%
1.1111111111
 
< 0.1%
1114
4.7%
0.97619047621
 
< 0.1%
0.96551724142
 
0.1%

CMO
Numeric time series

High correlation 

Distinct2368
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5292575
Minimum-73.449264
Maximum79.937435
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:02.524609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-73.449264
5-th percentile-48.315512
Q1-17.703676
median2.0789897
Q323.815716
95-th percentile52.68091
Maximum79.937435
Range153.3867
Interquartile range (IQR)41.519392

Descriptive statistics

Standard deviation29.933809
Coefficient of variation (CV)11.835018
Kurtosis-0.49448745
Mean2.5292575
Median Absolute Deviation (MAD)20.768528
Skewness0.0032851614
Sum6082.8643
Variance896.0329
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value7.300576325 × 10-18
2026-02-01T22:34:02.630430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:02.896241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:03.779335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-32.502314933
 
0.1%
22.431493742
 
0.1%
29.269070932
 
0.1%
-20.674470882
 
0.1%
-56.011879192
 
0.1%
-48.771805792
 
0.1%
31.239334032
 
0.1%
38.53189422
 
0.1%
29.884792462
 
0.1%
44.916104032
 
0.1%
Other values (2358)2384
99.1%
ValueCountFrequency (%)
-73.449264291
< 0.1%
-71.063817661
< 0.1%
-69.355998621
< 0.1%
-68.309817611
< 0.1%
-68.100524551
< 0.1%
-66.975806851
< 0.1%
-66.680214271
< 0.1%
-66.567460051
< 0.1%
-66.563782511
< 0.1%
-66.32980891
< 0.1%
ValueCountFrequency (%)
79.937434551
< 0.1%
78.190994121
< 0.1%
77.651238051
< 0.1%
76.671613991
< 0.1%
76.414384531
< 0.1%
76.365101941
< 0.1%
73.526456921
< 0.1%
71.95514031
< 0.1%
71.677023291
< 0.1%
71.285077841
< 0.1%
2026-02-01T22:34:02.714948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MFI
Numeric time series

Distinct2403
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.530387
Minimum-1.0957529 × 10-14
Maximum100
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:04.273483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1.0957529 × 10-14
5-th percentile1.5576453
Q123.992965
median45.048832
Q371.247707
95-th percentile98.824987
Maximum100
Range100
Interquartile range (IQR)47.254742

Descriptive statistics

Standard deviation30.042472
Coefficient of variation (CV)0.63206873
Kurtosis-1.0584773
Mean47.530387
Median Absolute Deviation (MAD)22.981241
Skewness0.15245248
Sum114310.58
Variance902.55011
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value1.219512117 × 10-13
2026-02-01T22:34:04.375054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:04.634860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:05.289560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
76.578703482
 
0.1%
31.637016052
 
0.1%
74.08316511
 
< 0.1%
74.334094181
 
< 0.1%
74.362721851
 
< 0.1%
74.533812711
 
< 0.1%
74.636330651
 
< 0.1%
74.563600441
 
< 0.1%
74.606818691
 
< 0.1%
74.662147541
 
< 0.1%
Other values (2393)2393
99.5%
ValueCountFrequency (%)
-1.095752886 × 10-141
< 0.1%
-8.810004099 × 10-151
< 0.1%
0.019789667561
< 0.1%
0.020096619111
< 0.1%
0.021970416361
< 0.1%
0.022008852031
< 0.1%
0.022394334171
< 0.1%
0.022488963661
< 0.1%
0.024152764441
< 0.1%
0.035441988641
< 0.1%
ValueCountFrequency (%)
1001
< 0.1%
1001
< 0.1%
1001
< 0.1%
99.996400611
< 0.1%
99.995998861
< 0.1%
99.994792571
< 0.1%
99.994780221
< 0.1%
99.994773811
< 0.1%
99.99475741
< 0.1%
99.994696541
< 0.1%
2026-02-01T22:34:04.460420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ROC
Numeric time series

High correlation 

Distinct2304
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1692349
Minimum-14.9375
Maximum12.128563
Zeros21
Zeros (%)0.9%
Memory size37.6 KiB
2026-02-01T22:34:05.979821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-14.9375
5-th percentile-4.8924753
Q1-1.6491754
median0.23023791
Q32.1194605
95-th percentile5.0326816
Maximum12.128563
Range27.066063
Interquartile range (IQR)3.7686359

Descriptive statistics

Standard deviation3.0856306
Coefficient of variation (CV)18.232827
Kurtosis1.2548739
Mean0.1692349
Median Absolute Deviation (MAD)1.8818896
Skewness-0.28562723
Sum407.00992
Variance9.521116
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value4.223008783 × 10-16
2026-02-01T22:34:06.080857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:06.335313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:06.996714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
021
 
0.9%
-3.8639876353
 
0.1%
-2.7027027033
 
0.1%
-1.6042780753
 
0.1%
-1.891074132
 
0.1%
1.1735121542
 
0.1%
0.45558086562
 
0.1%
-4.1631973362
 
0.1%
-1.9638648862
 
0.1%
2.5735294122
 
0.1%
Other values (2294)2363
98.3%
ValueCountFrequency (%)
-14.93751
< 0.1%
-12.119013061
< 0.1%
-12.04419891
< 0.1%
-11.936507941
< 0.1%
-11.75198271
< 0.1%
-11.745689661
< 0.1%
-11.637931031
< 0.1%
-11.428571431
< 0.1%
-11.403508771
< 0.1%
-11.160151321
< 0.1%
ValueCountFrequency (%)
12.128562771
< 0.1%
11.827956991
< 0.1%
11.021505381
< 0.1%
10.467836261
< 0.1%
10.278637771
< 0.1%
9.8429951691
< 0.1%
9.4292803971
< 0.1%
8.5261875761
< 0.1%
8.4620135891
< 0.1%
8.431494111
< 0.1%
2026-02-01T22:34:06.162709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WILLR
Numeric time series

High correlation  Zeros 

Distinct1451
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-47.655748
Minimum-100
Maximum8.6614173
Zeros72
Zeros (%)3.0%
Memory size37.6 KiB
2026-02-01T22:34:07.413672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-96.363636
Q1-77.358491
median-46.511628
Q3-16.513761
95-th percentile-2
Maximum8.6614173
Range108.66142
Interquartile range (IQR)60.844729

Descriptive statistics

Standard deviation32.124163
Coefficient of variation (CV)-0.67408789
Kurtosis-1.3835696
Mean-47.655748
Median Absolute Deviation (MAD)30.411449
Skewness-0.073122904
Sum-114612.07
Variance1031.9618
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value6.844040262 × 10-24
2026-02-01T22:34:07.858118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:08.111166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:08.837143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-072
 
3.0%
-10051
 
2.1%
-5012
 
0.5%
-15.3846153811
 
0.5%
-1011
 
0.5%
-7510
 
0.4%
-208
 
0.3%
-808
 
0.3%
-84.615384628
 
0.3%
-608
 
0.3%
Other values (1441)2206
91.7%
ValueCountFrequency (%)
-1001
 
< 0.1%
-10051
2.1%
-1001
 
< 0.1%
-99.465240641
 
< 0.1%
-99.295774651
 
< 0.1%
-99.275362321
 
< 0.1%
-99.107142861
 
< 0.1%
-99.082568811
 
< 0.1%
-98.989898991
 
< 0.1%
-98.952879581
 
< 0.1%
ValueCountFrequency (%)
8.6614173231
 
< 0.1%
21
 
< 0.1%
-072
3.0%
-0.86956521741
 
< 0.1%
-0.91743119271
 
< 0.1%
-0.94339622642
 
0.1%
-0.97087378641
 
< 0.1%
-1.010101011
 
< 0.1%
-1.0989010992
 
0.1%
-1.1235955062
 
0.1%
2026-02-01T22:34:07.937835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

AD
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2145
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-110035.74
Minimum-858702.76
Maximum1008908.6
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:09.350372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-858702.76
5-th percentile-671567.76
Q1-367266.89
median-124241.89
Q393802.548
95-th percentile508949.54
Maximum1008908.6
Range1867611.4
Interquartile range (IQR)461069.44

Descriptive statistics

Standard deviation378988.72
Coefficient of variation (CV)-3.4442329
Kurtosis0.076180596
Mean-110035.74
Median Absolute Deviation (MAD)230350.63
Skewness0.28854169
Sum-2.6463596 × 108
Variance1.4363245 × 1011
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.351338046
2026-02-01T22:34:09.451918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:09.708459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:10.358462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-166.25681639
 
0.4%
-151098.93266
 
0.2%
-17079.085585
 
0.2%
3030.5725255
 
0.2%
-124733.71075
 
0.2%
-125267.6325
 
0.2%
-366999.73695
 
0.2%
3997.6100824
 
0.2%
-130506.81844
 
0.2%
72236.945944
 
0.2%
Other values (2135)2353
97.8%
ValueCountFrequency (%)
-858702.76211
< 0.1%
-856110.05331
< 0.1%
-854953.40911
< 0.1%
-854829.5271
< 0.1%
-854483.05331
< 0.1%
-854343.09841
< 0.1%
-854301.921
< 0.1%
-854124.54281
< 0.1%
-853909.60171
< 0.1%
-853587.21711
< 0.1%
ValueCountFrequency (%)
1008908.5941
< 0.1%
1008678.261
< 0.1%
1008540.461
< 0.1%
1008521.261
< 0.1%
1008483.6451
< 0.1%
1008226.7311
< 0.1%
1008163.3021
< 0.1%
1008119.7171
< 0.1%
1008119.1271
< 0.1%
1008110.7171
< 0.1%
2026-02-01T22:34:09.534913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

OBV
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2215
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-840302.08
Minimum-2508726
Maximum338110
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:10.858827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2508726
5-th percentile-2230157.4
Q1-1514641
median-669296
Q3-97012
95-th percentile302532.4
Maximum338110
Range2846836
Interquartile range (IQR)1417629

Descriptive statistics

Standard deviation824435.69
Coefficient of variation (CV)-0.98111823
Kurtosis-1.2163824
Mean-840302.08
Median Absolute Deviation (MAD)683269
Skewness-0.34466162
Sum-2.0209265 × 109
Variance6.796942 × 1011
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.7827156457
2026-02-01T22:34:10.956693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:11.209560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:11.817512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-24858306
 
0.2%
-22304274
 
0.2%
-21704433
 
0.1%
-19371543
 
0.1%
-21704773
 
0.1%
-1510443
 
0.1%
-12945003
 
0.1%
-4490733
 
0.1%
-25074043
 
0.1%
-16617253
 
0.1%
Other values (2205)2371
98.6%
ValueCountFrequency (%)
-25087261
< 0.1%
-25087171
< 0.1%
-25086131
< 0.1%
-25085101
< 0.1%
-25084761
< 0.1%
-25083891
< 0.1%
-25082091
< 0.1%
-25080141
< 0.1%
-25079381
< 0.1%
-25076391
< 0.1%
ValueCountFrequency (%)
3381101
< 0.1%
3381071
< 0.1%
3380811
< 0.1%
3380381
< 0.1%
3380261
< 0.1%
3379711
< 0.1%
3379321
< 0.1%
3379251
< 0.1%
3379141
< 0.1%
3379041
< 0.1%
2026-02-01T22:34:11.038733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

NATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1826772
Minimum0.51060091
Maximum3.3357371
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:12.335044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.51060091
5-th percentile0.65749836
Q10.87590545
median1.1236643
Q31.3836067
95-th percentile1.9376016
Maximum3.3357371
Range2.8251362
Interquartile range (IQR)0.50770121

Descriptive statistics

Standard deviation0.41739218
Coefficient of variation (CV)0.35292147
Kurtosis2.4726575
Mean1.1826772
Median Absolute Deviation (MAD)0.25338117
Skewness1.2744234
Sum2844.3387
Variance0.17421623
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0007067519461
2026-02-01T22:34:12.442055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:12.709978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:13.402480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.4632355671
 
< 0.1%
1.4685176921
 
< 0.1%
1.5151786581
 
< 0.1%
1.5203731461
 
< 0.1%
1.5790200261
 
< 0.1%
1.5642726321
 
< 0.1%
1.5632507971
 
< 0.1%
1.8683098771
 
< 0.1%
1.9075153561
 
< 0.1%
1.8887148221
 
< 0.1%
Other values (2395)2395
99.6%
ValueCountFrequency (%)
0.5106009051
< 0.1%
0.51700034051
< 0.1%
0.52189032011
< 0.1%
0.52441196081
< 0.1%
0.54071206291
< 0.1%
0.54393056671
< 0.1%
0.5496190961
< 0.1%
0.55173591461
< 0.1%
0.55354449271
< 0.1%
0.56523963461
< 0.1%
ValueCountFrequency (%)
3.3357370851
< 0.1%
3.3026051181
< 0.1%
3.148658231
< 0.1%
3.1375448041
< 0.1%
3.130018621
< 0.1%
3.0534006771
< 0.1%
3.0315445841
< 0.1%
3.0218328231
< 0.1%
2.930656011
< 0.1%
2.8882092021
< 0.1%
2026-02-01T22:34:12.530863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.064033
Minimum6.5407976
Maximum54.526011
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:13.759256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.5407976
5-th percentile8.3268852
Q111.334906
median14.813015
Q318.405133
95-th percentile29.462929
Maximum54.526011
Range47.985213
Interquartile range (IQR)7.0702272

Descriptive statistics

Standard deviation6.9515682
Coefficient of variation (CV)0.43274116
Kurtosis5.2529758
Mean16.064033
Median Absolute Deviation (MAD)3.4977998
Skewness1.8973854
Sum38633.999
Variance48.324301
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.004378361206
2026-02-01T22:34:13.994172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:14.253763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:15.042497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
16.066326531
 
< 0.1%
15.918731781
 
< 0.1%
16.424536651
 
< 0.1%
16.465641181
 
< 0.1%
17.432381091
 
< 0.1%
17.47292531
 
< 0.1%
17.367716351
 
< 0.1%
19.84145091
 
< 0.1%
20.067061551
 
< 0.1%
20.133700011
 
< 0.1%
Other values (2395)2395
99.6%
ValueCountFrequency (%)
6.5407975931
< 0.1%
6.6331143691
< 0.1%
6.6593204851
< 0.1%
6.681008381
< 0.1%
6.7775545561
< 0.1%
6.8373664451
< 0.1%
6.9535571291
< 0.1%
6.9895077811
< 0.1%
7.0410859481
< 0.1%
7.0556254021
< 0.1%
ValueCountFrequency (%)
54.52601051
< 0.1%
53.104934391
< 0.1%
50.850830421
< 0.1%
50.702724041
< 0.1%
50.581100891
< 0.1%
50.07577111
< 0.1%
49.497621651
< 0.1%
49.111022261
< 0.1%
48.531663521
< 0.1%
48.08315171
< 0.1%
2026-02-01T22:34:14.076392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

TRANGE
Real number (ℝ)

High correlation 

Distinct77
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.079834
Minimum0
Maximum163
Zeros7
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:15.531431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q18
median13
Q320
95-th percentile38
Maximum163
Range163
Interquartile range (IQR)12

Descriptive statistics

Standard deviation12.495102
Coefficient of variation (CV)0.7770666
Kurtosis17.979454
Mean16.079834
Median Absolute Deviation (MAD)6
Skewness3.0329666
Sum38672
Variance156.12757
MonotonicityNot monotonic
2026-02-01T22:34:15.731276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8132
 
5.5%
10132
 
5.5%
11130
 
5.4%
9125
 
5.2%
12123
 
5.1%
5111
 
4.6%
7109
 
4.5%
14108
 
4.5%
6104
 
4.3%
13100
 
4.2%
Other values (67)1231
51.2%
ValueCountFrequency (%)
07
 
0.3%
124
 
1.0%
232
 
1.3%
346
 
1.9%
467
2.8%
5111
4.6%
6104
4.3%
7109
4.5%
8132
5.5%
9125
5.2%
ValueCountFrequency (%)
1631
 
< 0.1%
1211
 
< 0.1%
1051
 
< 0.1%
1031
 
< 0.1%
1021
 
< 0.1%
1001
 
< 0.1%
991
 
< 0.1%
941
 
< 0.1%
843
0.1%
813
0.1%

TSF
Numeric time series

High correlation  Non stationary 

Distinct2364
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.7808
Minimum1056.6923
Maximum1888.4725
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:34:15.834296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1056.6923
5-th percentile1119.7077
Q11220.6484
median1291.5385
Q31406.7582
95-th percentile1720.7121
Maximum1888.4725
Range831.78022
Interquartile range (IQR)186.10989

Descriptive statistics

Standard deviation181.1679
Coefficient of variation (CV)0.13491994
Kurtosis0.10904671
Mean1342.7808
Median Absolute Deviation (MAD)81.802198
Skewness0.99088528
Sum3229387.8
Variance32821.808
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3959987156
2026-02-01T22:34:15.925644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:34:16.209509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 13 minutes
std8 hours, 19 minutes and 51.76 seconds
2026-02-01T22:34:17.086560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1246.6923082
 
0.1%
1673.0989012
 
0.1%
1318.6263742
 
0.1%
1339.6373632
 
0.1%
1341.5934072
 
0.1%
1220.3186812
 
0.1%
1286.6043962
 
0.1%
1244.7252752
 
0.1%
1283.6813192
 
0.1%
1193.7032972
 
0.1%
Other values (2354)2385
99.2%
ValueCountFrequency (%)
1056.6923081
< 0.1%
1057.3406591
< 0.1%
1058.0329671
< 0.1%
1058.1868131
< 0.1%
1058.5164841
< 0.1%
1059.2087911
< 0.1%
1060.5934071
< 0.1%
1061.2417581
< 0.1%
1061.2527471
< 0.1%
1061.4285711
< 0.1%
ValueCountFrequency (%)
1888.4725271
< 0.1%
1875.3516481
< 0.1%
1864.219781
< 0.1%
1863.4615381
< 0.1%
1855.8681321
< 0.1%
1852.9340661
< 0.1%
1850.2857141
< 0.1%
1848.9230771
< 0.1%
1839.4945051
< 0.1%
1838.3626371
< 0.1%
2026-02-01T22:34:16.031906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-01T22:33:50.395631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:32.993592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.948108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.964830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.245111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.310427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.579512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.719042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.719791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.765851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.598098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.791330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.858007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.025628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.989827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.159916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.248616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.447244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.046005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.009693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.009895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.312445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.369542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.639223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.774346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.782647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.809641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.651691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.851084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.919128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.085552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.041359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.214750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.307870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.506451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.103629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.075844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.060774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.377100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.432917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.708798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.834003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.853650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.858513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.713287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.915905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.988189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.151622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.099895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.277511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.374899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.601874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.162083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.142969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.340435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.443332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.499631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.776654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.892118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.922895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.907482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.778993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.984099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.052715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.220105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.159664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.339024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.440739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.663461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.218946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.210007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.408036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.507840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.563725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.845568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.946448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.993767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.956950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.973883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.051453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:33:46.284023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.219761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.401496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.508084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.723153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.274937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.278917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.473768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.573785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.659928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.913942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.997824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.062841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.007749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.049934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.114127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.177150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:33:47.284989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.463385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.574089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.786110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.332946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.344851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.540895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.637907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.725493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.984757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.048608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.133743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:33:47.474065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.652758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.770402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.072921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.497258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.533142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.734029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.809347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.054436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.189509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.182531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.327591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.199484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.298395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.365178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.403526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.573914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.530053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.714449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.831366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.131939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.551747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.589847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.798785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.864683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.120293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.256834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.228334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.388132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.245144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.356457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.427082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.562851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.625435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.585991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.798752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.895547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.191664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.604884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.646056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.862995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.917659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.184431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.321038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.272656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.446702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.292566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.418303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.487271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.628001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.677718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.637062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.881626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.979287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.257194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.663290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.702701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.932124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.972114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.256433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.394804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.321110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.506032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.343116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.484982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.555473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.696066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.732494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.695848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:48.965711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.049995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.319530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.721732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.759471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:35.995341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.064395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.321128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.460006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.483425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.561936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.391201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.546494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.616463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.762315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.783314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.754544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.024596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.114496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.377397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.778354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.813768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.060488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.125408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.386330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.526015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.541910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.614703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.442229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.607794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.677795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.828859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.835799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.820346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.079635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.180068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.438990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.835495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.864419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.121394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.184275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.448467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.587450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.599896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.664681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.490585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.665369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.735882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.892013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.883388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.878989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.133536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.245279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:51.504566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:33.896451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:34.918377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:36.190316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:37.252744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:38.519084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:39.659856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:40.663561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:41.717582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:42.547948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:43.734177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:44.800869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:45.964001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:46.940232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:47.943782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:49.194732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:50.335805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T22:34:17.518178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ADATRBOPCMOEMAKAMAMAMFIMidPriceNATROBVROCTRANGETSFWILLRWMAclose
AD1.0000.3940.0360.0850.7070.7070.7040.1200.7000.1490.5110.0450.2270.6980.1020.7050.704
ATR0.3941.0000.0170.0030.4410.4440.4420.1060.4400.9260.5970.0010.5770.4340.0060.4400.434
BOP0.0360.0171.0000.3300.0250.0230.0180.0670.020-0.0090.0470.2570.0230.0370.3900.0260.081
CMO0.0850.0030.3301.0000.0890.0770.0730.3920.070-0.0650.0680.8680.0400.1910.9120.1130.204
EMA0.7070.4410.0250.0891.0000.9980.9990.0920.9980.1160.3680.0450.2520.9880.0470.9990.989
KAMA0.7070.4440.0230.0770.9981.0000.9970.0860.9960.1200.3770.0350.2530.9850.0340.9970.986
MA0.7040.4420.0180.0730.9990.9971.0000.0910.9990.1180.3670.0270.2520.9860.0280.9980.984
MFI0.1200.1060.0670.3920.0920.0860.0911.0000.0870.0640.1480.3120.0770.1470.3330.1060.133
MidPrice0.7000.4400.0200.0700.9980.9960.9990.0871.0000.1160.3620.0180.2510.9830.0200.9970.984
NATR0.1490.926-0.009-0.0650.1160.1200.1180.0640.1161.0000.497-0.0470.5460.107-0.0540.1140.106
OBV0.5110.5970.0470.0680.3680.3770.3670.1480.3620.4971.0000.0360.3080.3630.0820.3670.367
ROC0.0450.0010.2570.8680.0450.0350.0270.3120.018-0.0470.0361.0000.0360.1560.8690.0700.152
TRANGE0.2270.5770.0230.0400.2520.2530.2520.0770.2510.5460.3080.0361.0000.2530.0210.2530.251
TSF0.6980.4340.0370.1910.9880.9850.9860.1470.9830.1070.3630.1560.2531.0000.1420.9930.992
WILLR0.1020.0060.3900.9120.0470.0340.0280.3330.020-0.0540.0820.8690.0210.1421.0000.0670.164
WMA0.7050.4400.0260.1130.9990.9970.9980.1060.9970.1140.3670.0700.2530.9930.0671.0000.991
close0.7040.4340.0810.2040.9890.9860.9840.1330.9840.1060.3670.1520.2510.9920.1640.9911.000

Missing values

2026-02-01T22:33:51.607828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T22:33:51.710075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2010-01-262010-01-261098False1117.51111.4562151120.8069371108.9090911120.00.000000-14.51243064.344824-4.604692-80.769231533.647374609.01.46323616.0663273.01094.527473
2010-01-272010-01-271084False1113.01106.4641761117.3009581102.8181821114.50.000000-25.7728770.175892-3.985828-98.717949533.647374-206085.01.46851815.91873214.01085.307692
2010-01-282010-01-281084False1107.81102.3797801112.8500491097.5454551109.5-0.173913-25.77287732.909960-4.577465-87.500000-3864.961322-206085.01.51517916.42453723.01077.274725
2010-01-292010-01-291083False1101.81098.8561841107.2488471093.0363641106.5-0.117647-26.62516531.721390-5.249344-88.636364-3191.078969-217541.01.52037316.46564117.01071.450549
2010-02-012010-02-011104False1099.21099.7914231107.1025361093.4363641106.50.7666670.13137432.206771-2.300885-63.095238-1229.478969-215089.01.57902017.43238130.01075.725275
2010-02-022010-02-021117False1096.91102.9202551107.4657851096.6727271103.00.00000012.80454632.922147-2.017544-39.7260271726.965476-211763.01.56427317.47292518.01081.395604
2010-02-032010-02-031111False1096.81104.3893001107.4838211099.2363641099.0-0.3125005.91219233.108526-0.089928-47.9452051087.215476-212616.01.56325117.36771616.01086.978022
2010-02-042010-02-041062False1092.71096.6821541104.4348131092.9090911092.0-0.923077-31.86409932.947987-3.717135-96.296296-174.246063-214042.01.86831019.84145152.01080.615385
2010-02-052010-02-051052False1089.01088.5581261101.2706691085.5090911085.00.000000-36.96249732.762926-3.397612-92.631579-939.637367-215998.01.90751520.06706223.01071.780220
2010-02-082010-02-081066False1086.11084.4566491099.8904771081.3272731085.00.000000-22.68256532.868277-2.648402-76.136364-1089.364640-215449.01.88871520.13370021.01071.274725
Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2019-08-062019-08-061472False1433.51439.8680641432.0690591442.0181821438.00.11764757.81015398.1326283.661972-4.05405477865.538041-1684836.01.15140516.94867817.01452.197802
2019-08-072019-08-071507False1441.91452.0738711449.7690141455.3818181455.50.89189270.93537198.1374805.903022-2.75229478555.916419-1684012.01.22444218.45234438.01473.131868
2019-08-082019-08-081498False1450.31460.4240761461.1619881465.5818181455.50.00000056.98196398.1396825.940594-11.00917478464.166419-1684379.01.22010518.27717616.01488.648352
2019-08-092019-08-091497False1458.21467.0742441469.1155831474.0727271455.5-0.75000055.41572398.1404715.571227-11.92660678402.499752-1684453.01.19096917.82880612.01501.472527
2019-08-122019-08-121505False1466.71473.9698361477.4052911482.5818181458.00.33333359.04763398.1436915.985915-8.77193078469.129382-1684196.01.22816618.48389227.01513.329670
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